Chapter 7. Risk Difference Methods for Closed Cohort Data
Published Online: 31 MAR 2003
DOI: 10.1002/0471272612.ch7
Copyright © 2001 John Wiley & Sons, Inc.
Book Title
Biostatistical Methods in Epidemiology
Additional Information
How to Cite
Newman, S. C. (2003) Risk Difference Methods for Closed Cohort Data, in Biostatistical Methods in Epidemiology, John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/0471272612.ch7
Publication History
- Published Online: 31 MAR 2003
- Published Print: 11 JAN 2002
Book Series:
Book Series Editors:
- David J. Balding,
- Peter Bloomfield,
- Noel A.C. Cressie,
- Nicholas I. Fisher,
- Iain M. Johnstone,
- J.B. Kadane,
- Louise M. Ryan,
- David W. Scott,
- Adrian F.M. Smith,
- Jozef L. Teugels
ISBN Information
Print ISBN: 9780471369141
Online ISBN: 9780471272618
- Summary
- Chapter
Keywords:
- risk difference;
- exact;
- asymptotic;
- weighted least squares;
- Mantel–Haenszel
Summary
This chapter presents risk difference methods for analyzing unstratified and stratified data from a closed cohort study in which there are two or more exposure categories. One of the aims is to compare asymptotic unconditional, Mantel–Haenszel, and weighted least squares methods, and to demonstrate that in many applications the various methods produce similar numerical results. Recommendations are provided for choosing methods for particular situations.
The section and subsection headings of the chapter are as follows:
Asymptotic Unconditional Methods for a Single 2 × 2 Table
Asymptotic Unconditional Methods for J (2 × 2) Tables
Point Estimates and Fitted Counts
Confidence Interval
Wald and Likelihood Ratio Tests of Association
Likelihood Ratio Test of Homogeneity
Mantel–Haenszel Estimate of the Risk Difference
Weighted Least Squares Methods for J (2 × 2) Tables
Summary of Examples and Recommendations